arXiv (All)
open access
A shape-similarity latent space for fluid interfaces: invertible reduced-order modelling of droplet morphology
A droplet breaks up in tens of microseconds, and a recording captures perhaps a dozen frames. The states in between cannot be recovered without repeating the experiment, and simulating them is too costly to sweep an operating envelope. Yet they are present in the corpus as a whole: a campaign spanni
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Elastocapillary morphing of self-encapsulated droplets floating at the oil-air interface#926030
- SplashSplat: Reconstructing Splashing Liquids from Real-World Multi-View Videos#1034608
- Statistics and morphologies of stable droplets in scalar active fluids#652101
- Statistics and morphologies of stable droplets in scalar active fluids#650648
- Flow Sampling: Learning to Sample from Unnormalized Densities via Denoising Conditional Processes#155274
Record · ID 1142250
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive